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Binary Spiking Neural Networks as Causal Models
二元脉冲神经网络如何从结构上实现因果建模，这篇论文给出了理论框架与可行路径
arXiv:2604.27007v2 Announce Type: replace Abstract: We provide a causal analysis of Binary Spiking Neural Networks (BSNNs) to explain their behavior. …
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NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
脉冲神经网络的局部学习规则综述与基准测试框架，助你快速理解不同训练算法的差异与适配场景
arXiv:2605.15058v1 Announce Type: cross Abstract: The rapid expansion of spiking neural networks (SNNs) has led to a proliferation of training algorit…
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Elastic Spiking Transformers for Efficient Gesture Understanding
新型弹性脉冲 Transformer，突破静态网络限制，在神经形态硬件上高效理解手势。
arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing…
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Scalable neuromorphic computing from autonomous spiking dynamics in a clockless reconfigurable chip
无时钟异步电路驱动的可扩展神经形态计算架构，在FPGA上实现布尔脉冲神经元网络，突破传统时钟同步限制。
arXiv:2605.16114v1 Announce Type: cross Abstract: We propose a scalable neuromorphic architecture based on spiking dynamics emerging from the autonomo…
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BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation
脉冲语言模型新突破：无Softmax注意力与对齐蒸馏打造超低能耗大模型。
arXiv:2605.13859v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer promising energy-efficient alternatives to large language model…